{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WKSRT7MANFEAEVWVH7CBSESCZU","short_pith_number":"pith:WKSRT7MA","canonical_record":{"source":{"id":"2503.16420","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T17:59:40Z","cross_cats_sorted":[],"title_canon_sha256":"03e30a1c050960df37e367c2573705a32241b56d86304dd0119b808dc2789449","abstract_canon_sha256":"1b591dd6d162573c60b716d375660513aa888da6e92a7624d86b2ecf65643928"},"schema_version":"1.0"},"canonical_sha256":"b2a519fd8069480256d53fc4191242cd3711ae1a15eb51ce63dd1795711bd87c","source":{"kind":"arxiv","id":"2503.16420","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.16420","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"arxiv_version","alias_value":"2503.16420v1","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.16420","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_12","alias_value":"WKSRT7MANFEA","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_16","alias_value":"WKSRT7MANFEAEVWV","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_8","alias_value":"WKSRT7MA","created_at":"2026-07-05T10:36:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WKSRT7MANFEAEVWVH7CBSESCZU","target":"record","payload":{"canonical_record":{"source":{"id":"2503.16420","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T17:59:40Z","cross_cats_sorted":[],"title_canon_sha256":"03e30a1c050960df37e367c2573705a32241b56d86304dd0119b808dc2789449","abstract_canon_sha256":"1b591dd6d162573c60b716d375660513aa888da6e92a7624d86b2ecf65643928"},"schema_version":"1.0"},"canonical_sha256":"b2a519fd8069480256d53fc4191242cd3711ae1a15eb51ce63dd1795711bd87c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:36:19.079919Z","signature_b64":"oDPPDam5a6JMiBASpkgAF3YRhd+kNc9uakEUDSyxa0ThRrhyowkKSL9gBSQJbH2HxzOTl9o21GtZ4Fu4vcMPBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2a519fd8069480256d53fc4191242cd3711ae1a15eb51ce63dd1795711bd87c","last_reissued_at":"2026-07-05T10:36:19.078970Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:36:19.078970Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.16420","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:36:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S4uow4InhS0qQE9fg7frVkpzsyB01WhTO/tWCOZMzlOHOD0FFBoqs/5O+yhY9ayb8+8b524QgRkoVyPFYyt9DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:19:59.654158Z"},"content_sha256":"b3c61d534320152c3a75b8d292ac2d6603e01cce4fd249d008cc173acba2ea97","schema_version":"1.0","event_id":"sha256:b3c61d534320152c3a75b8d292ac2d6603e01cce4fd249d008cc173acba2ea97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WKSRT7MANFEAEVWVH7CBSESCZU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SynCity: Training-Free Generation of 3D Worlds","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aleksandar Shtedritski, Andrea Vedaldi, Christian Rupprecht, Iro Laina, Paul Engstler","submitted_at":"2025-03-20T17:59:40Z","abstract_excerpt":"We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic versatility of 2D image generators to create large, high-quality 3D spaces. While most 3D generative models are object-centric and cannot generate large-scale worlds, we show how 3D and 2D generators can be combined to generate ever-expanding scenes. Through a tile-based approach, we allow fine-grained control over the layout and the appearance of scenes. The world"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.16420","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2503.16420/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:36:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KTg9k/s/S+Ao/c6eZihYCsDYv/9dOiCnv0zmJcBufbVeoygBRlNCw4DPiAUHeNDb7ct8o1Ih80ZOkFIhiRG/CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:19:59.655116Z"},"content_sha256":"e243a11d5eadd47f37d88c9a5fdbb347ffeba3ab9d0791c331cb4293b58608c0","schema_version":"1.0","event_id":"sha256:e243a11d5eadd47f37d88c9a5fdbb347ffeba3ab9d0791c331cb4293b58608c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WKSRT7MANFEAEVWVH7CBSESCZU/bundle.json","state_url":"https://pith.science/pith/WKSRT7MANFEAEVWVH7CBSESCZU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WKSRT7MANFEAEVWVH7CBSESCZU/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T23:19:59Z","links":{"resolver":"https://pith.science/pith/WKSRT7MANFEAEVWVH7CBSESCZU","bundle":"https://pith.science/pith/WKSRT7MANFEAEVWVH7CBSESCZU/bundle.json","state":"https://pith.science/pith/WKSRT7MANFEAEVWVH7CBSESCZU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WKSRT7MANFEAEVWVH7CBSESCZU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WKSRT7MANFEAEVWVH7CBSESCZU","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"1b591dd6d162573c60b716d375660513aa888da6e92a7624d86b2ecf65643928","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T17:59:40Z","title_canon_sha256":"03e30a1c050960df37e367c2573705a32241b56d86304dd0119b808dc2789449"},"schema_version":"1.0","source":{"id":"2503.16420","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.16420","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"arxiv_version","alias_value":"2503.16420v1","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.16420","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_12","alias_value":"WKSRT7MANFEA","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_16","alias_value":"WKSRT7MANFEAEVWV","created_at":"2026-07-05T10:36:19Z"},{"alias_kind":"pith_short_8","alias_value":"WKSRT7MA","created_at":"2026-07-05T10:36:19Z"}],"graph_snapshots":[{"event_id":"sha256:e243a11d5eadd47f37d88c9a5fdbb347ffeba3ab9d0791c331cb4293b58608c0","target":"graph","created_at":"2026-07-05T10:36:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.16420/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic versatility of 2D image generators to create large, high-quality 3D spaces. While most 3D generative models are object-centric and cannot generate large-scale worlds, we show how 3D and 2D generators can be combined to generate ever-expanding scenes. Through a tile-based approach, we allow fine-grained control over the layout and the appearance of scenes. The world","authors_text":"Aleksandar Shtedritski, Andrea Vedaldi, Christian Rupprecht, Iro Laina, Paul Engstler","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T17:59:40Z","title":"SynCity: Training-Free Generation of 3D Worlds"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.16420","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b3c61d534320152c3a75b8d292ac2d6603e01cce4fd249d008cc173acba2ea97","target":"record","created_at":"2026-07-05T10:36:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"1b591dd6d162573c60b716d375660513aa888da6e92a7624d86b2ecf65643928","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-20T17:59:40Z","title_canon_sha256":"03e30a1c050960df37e367c2573705a32241b56d86304dd0119b808dc2789449"},"schema_version":"1.0","source":{"id":"2503.16420","kind":"arxiv","version":1}},"canonical_sha256":"b2a519fd8069480256d53fc4191242cd3711ae1a15eb51ce63dd1795711bd87c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b2a519fd8069480256d53fc4191242cd3711ae1a15eb51ce63dd1795711bd87c","first_computed_at":"2026-07-05T10:36:19.078970Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:36:19.078970Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oDPPDam5a6JMiBASpkgAF3YRhd+kNc9uakEUDSyxa0ThRrhyowkKSL9gBSQJbH2HxzOTl9o21GtZ4Fu4vcMPBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:36:19.079919Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.16420","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3c61d534320152c3a75b8d292ac2d6603e01cce4fd249d008cc173acba2ea97","sha256:e243a11d5eadd47f37d88c9a5fdbb347ffeba3ab9d0791c331cb4293b58608c0"],"state_sha256":"e57c664b376f32e58d27b0319c697efa296b15cbe2b60fd4b9b6cad68e657372"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KNwC42zdc1XowTkQF08bTBwibrTWHTpvcYCFTqGPMkVntl9OQVVq64mR1o+v9/JIXjFOCgDvNCef1bhaXgLiDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T23:19:59.678399Z","bundle_sha256":"6f8e78a406ce4a17b6451fff52973ad11d323606f22cba36187b0773fd4b12cc"}}